Sampling the spatial patterns of cancer: Optimized biopsy procedures for estimating prostate cancer volume and Gleason Score

This publication has 32 references indexed in Scilit:

• Improved Detection of Clinically Significant, Curable Prostate Cancer With Systematic 12-Core Biopsy
  Journal of Urology, 2004
• Construction of an abdominal probabilistic atlas and its application in segmentation
  IEEE Transactions on Medical Imaging, 2003
• Automatic construction of multiple-object three-dimensional statistical shape models: application to cardiac modeling
  IEEE Transactions on Medical Imaging, 2002
• Prostate cancer detection with two sets of ten-core compared with two sets of sextant biopsies
  Urology, 2001
• How accurately does prostate biopsy Gleason score predict pathologic findings and disease free survival?
  The Prostate, 2001
• An adaptive-focus statistical shape model for segmentation and shape modeling of 3-D brain structures
  IEEE Transactions on Medical Imaging, 2001
• Support vector machine classification and validation of cancer tissue samples using microarray expression data
  Bioinformatics, 2000
• Is Systematic Sextant Biopsy Suitable for the Detection of Clinically Significant Prostate Cancer?
  Urologia Internationalis, 2000
• Detection rate of histologically insignificant prostate cancer with systematic sextant biopsies and fine needle aspiration cytology.
  2000
• The percent of cores positive for cancer in prostate needle biopsy specimens is strongly predictive of tumor stage and volume at radical prostatectomy.
  2000